This advanced Retrieval-Augmented Generation (RAG) automation template for n8n enables contextual, real-time recommendations using Slack messages as input. The workflow extracts referenced documents from Google Drive, performs semantic retrieval from Pinecone, and generates next-step advice using GPT-4o — tailored specifically for executives and knowledge workers.
Perfect for AI copilots, Slack-based assistants, or CTO coaching tools, this no-code RAG implementation gives you the building blocks to combine unstructured inputs with memory-augmented intelligence.
What This Template Does
✅ Triggers from a Slack Message or Mention
Monitors a Slack channel using a bot, capturing user input in real-time.
🔍 Extracts Key Info from Message
GPT-4o parses the message to identify the subject person and Google Drive link (if present).
📥 Downloads File from Google Drive
Automatically fetches and extracts PDF content using the built-in extractor.
📇 Retrieves Metadata from Google Sheets & Pinecone
Looks up user ID from Google Sheets and retrieves context from Pinecone based on embeddings and reranking.
🧠 Contextual Response via GPT-4o (RAG)
Combines user data and document context to generate a single, actionable next step using a tightly scoped GPT-4o prompt.
🛠️ Auto-Fixes & Structures Output
Ensures formatted response with recommended_action, rationale, and optional risk_note.
📨 Sends Final Output Back to Slack
Posts the recommendation directly to the channel as a reply.
Required Integrations
Ideal Use Cases
🧑💼 Executive coaching bots (e.g., for CTOs or founders)
🧠 Slack-based internal AI assistants
📄 AI-powered document summarization with memory
💬 Actionable recommendations based on real Slack conversations
📊 Enterprise knowledge augmentation from vector DBs
Why This Template Stands Out